Acquisition of plant phenotypic information facilitates plant breeding, sheds light on gene
action, and can be applied to optimize the quality of agricultural and forestry products …

Early prediction of grain yield helps scientists to make better breeding decisions for wheat.
Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based …

The scarcity of water resources is one of the biggest problems restricting food production.
Crop water productivity (CWP) is a practical and quantifiable indicator for characterizing …

The rapid and efficient estimation of aboveground biomass (AGB) in maize proves
advantageous for growth assessment, grain quality and yield prediction, and timely field …

High-throughput estimation of phenotypic traits from UAV (unmanned aerial vehicle) images
is helpful to improve the screening efficiency of breeding maize. Accurately estimating …

Relative chlorophyll content (SPAD) is an important index for characterizing the nitrogen
nutrient status of plants. Continuous, rapid, nondestructive, and accurate estimation of SPAD …

Crop leaf area index (LAI) is one of the important indicators to evaluate crop growth and
guide field management, and can be used to predict crop yield. Spectral and thermal …

Accurately monitoring the crop water conditions (CWC) is vital for agricultural water
management. Traditional in situ measurements are limited by inefficiency and lack of spatial …

Yield prediction is of great significance in agricultural production. Remote sensing
technology based on unmanned aerial vehicles (UAVs) offers the capacity of non-intrusive …

The high proportion of soil background pixels in UAV remote sensing images is an important
reason for the uncertainty of high-precision leaf area index (LAI) estimation at early growth …